bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–04–09
twenty-two papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Targeting glutamine metabolism as a therapeutic strategy for cancer.
  2. MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.
  3. Generalized Tree Structure to Annotate Untargeted Metabolomics and Stable Isotope Tracing Data.
  4. Development of pseudo-targeted profiling of isotopic metabolomics using combined platform of high resolution mass spectrometry and triple quadrupole mass spectrometry with application of 13C6-glucose tracing in HepG2 cells.
  5. Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry.
  6. Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics.
  7. Stearoyl coenzyme A desaturase-1: multitasker in cancer, metabolism, and ferroptosis.
  8. Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers.
  9. Multiplatform Untargeted Metabolomics.
  10. Targeted lipidomics data of COVID-19 patients.
  11. MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics.
  12. Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.
  13. Global determination of reaction rates and lipid turnover kinetics in Mus musculus.
  14. Improved diagnostics of purine and pyrimidine metabolism disorders using LC-MS/MS and its clinical application.
  15. Triglyceride cycling enables modification of stored fatty acids.
  16. The role of amino acid metabolism alterations in pancreatic cancer: From mechanism to application.
  17. Lipidomic study and diagnosis of hepatocellular carcinoma tumor with rapid evaporative ionization mass spectrometry.
  18. The GAPDH redox switch safeguards reductive capacity and enables survival of stressed tumour cells.
  19. Malondialdehyde-Induced Post-Translational Modification of Human Hemoglobin.
  20. Identification of Protein Arginylation by Encapsulated N-Terminal Peptide Enrichment Method.
  21. Analysis of Arginylated Peptides by Subtractive Edman Degradation.
  22. A metabolomics approach to the validation of predictive metabolites and phenotypic expression in non-alcoholic fatty liver disease.
  1. Exp Mol Med. 2023 Apr 03.
    Targeting glutamine metabolism as a therapeutic strategy for cancer.
    Jonghwa Jin, Jun-Kyu Byun, Yeon-Kyung Choi, Keun-Gyu Park.
      Proliferating cancer cells rely largely on glutamine for survival and proliferation. Glutamine serves as a carbon source for the synthesis of lipids and metabolites via the TCA cycle, as well as a source of nitrogen for amino acid and nucleotide synthesis. To date, many studies have explored the role of glutamine metabolism in cancer, thereby providing a scientific rationale for targeting glutamine metabolism for cancer treatment. In this review, we summarize the mechanism(s) involved at each step of glutamine metabolism, from glutamine transporters to redox homeostasis, and highlight areas that can be exploited for clinical cancer treatment. Furthermore, we discuss the mechanisms underlying cancer cell resistance to agents that target glutamine metabolism, as well as strategies for overcoming these mechanisms. Finally, we discuss the effects of glutamine blockade on the tumor microenvironment and explore strategies to maximize the utility of glutamine blockers as a cancer treatment.
    DOI:  https://doi.org/10.1038/s12276-023-00971-9
  2. J Proteome Res. 2023 Apr 05.
    MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.
    Devon Kohler, Mateusz Staniak, Tsung-Heng Tsai, Ting Huang, Nicholas Shulman, Oliver M Bernhardt, Brendan X MacLean, Alexey I Nesvizhskii, Lukas Reiter, Eduard Sabido, Meena Choi, Olga Vitek.
      The MSstats R-Bioconductor family of packages is widely used for statistical analyses of quantitative bottom-up mass spectrometry-based proteomic experiments to detect differentially abundant proteins. It is applicable to a variety of experimental designs and data acquisition strategies and is compatible with many data processing tools used to identify and quantify spectral features. In the face of ever-increasing complexities of experiments and data processing strategies, the core package of the family, with the same name MSstats, has undergone a series of substantial updates. Its new version MSstats v4.0 improves the usability, versatility, and accuracy of statistical methodology, and the usage of computational resources. New converters integrate the output of upstream processing tools directly with MSstats, requiring less manual work by the user. The package's statistical models have been updated to a more robust workflow. Finally, MSstats' code has been substantially refactored to improve memory use and computation speed. Here we detail these updates, highlighting methodological differences between the new and old versions. An empirical comparison of MSstats v4.0 to its previous implementations, as well as to the packages MSqRob and DEqMS, on controlled mixtures and biological experiments demonstrated a stronger performance and better usability of MSstats v4.0 as compared to existing methods.
    Keywords:  Bioinformatics; Mass spectrometry; Quantitative proteomics; Statistical inference; Statistical modeling
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00834
  3. Anal Chem. 2023 Apr 05.
    Generalized Tree Structure to Annotate Untargeted Metabolomics and Stable Isotope Tracing Data.
    Shuzhao Li, Shujian Zheng.
      In untargeted metabolomics, multiple ions are often measured for each original metabolite, including isotopic forms and in-source modifications, such as adducts and fragments. Without prior knowledge of the chemical identity or formula, computational organization and interpretation of these ions is challenging, which is the deficit of previous software tools that perform the task using network algorithms. We propose here a generalized tree structure to annotate ions in relationships to the original compound and infer neutral mass. An algorithm is presented to convert mass distance networks to this tree structure with high fidelity. This method is useful for both regular untargeted metabolomics and stable isotope tracing experiments. It is implemented as a Python package (khipu) and provides a JSON format for easy data exchange and software interoperability. By generalized preannotation, khipu makes it feasible to connect metabolomics data with common data science tools and supports flexible experimental designs.
    DOI:  https://doi.org/10.1021/acs.analchem.2c05810
  4. J Chromatogr A. 2023 Mar 21. pii: S0021-9673(23)00149-8. [Epub ahead of print]1696 463923
    Development of pseudo-targeted profiling of isotopic metabolomics using combined platform of high resolution mass spectrometry and triple quadrupole mass spectrometry with application of 13C6-glucose tracing in HepG2 cells.
    Xueying Wang, Chengting Luo, Lina Xu, Yusong Wang, Lv Jun Guo, Yupei Jiao, Haiteng Deng, Xiaohui Liu.
      Isotope tracing assisted metabolic analysis is becoming a unique tool to understand metabolic regulation in cell biology and biomedical research. Targeted mass spectrometry analysis based on selected reaction monitoring (SRM) has been widely applied in isotope tracing experiment with the advantages of high sensitivity and broad linearity. However, its application for new pathway discovery is largely restrained by molecular coverage. To overcome this limitation, we describe a strategy called pseudo-targeted profiling of isotopic metabolomics (PtPIM) to expand the analysis of isotope labeled metabolites beyond the limit of known pathways and chemical standards. Pseudo-targeted metabolomics was first established with ion transitions and retention times transformed from high resolution (orbitrap) mass spectrometry. Isotope labeled MRM transitions were then generated according to chemical formulas of fragments, which were derived from accurate ion masses acquired by HRMS. An in-house software "PseudoIsoMRM" was developed to simulate isotope labeled ion transitions in batch mode and correct the interference of natural isotopologues. This PtPIM strategy was successfully applied to study 13C6-glucose traced HepG2 cells. As 313 molecules determined as analysis targets, a total of 4104 ion transitions were simulated to monitor 13C labeled metabolites in positive-negative switching mode of QQQ mass spectrometer with minimum dwell time of 0.3 ms achieved. A total of 68 metabolites covering glycolysis, TCA cycle, nucleotide biosynthesis, one-carbon metabolism and related derivatives were found to be labeled (> 2%) in HepG2 cells. Active pentose phosphate pathway was observed with diverse labeling status of glycolysis intermediates. Meanwhile, our PtPIM strategy revealed that rotenone severely suppressed mitochondrial function e.g. oxidative phosphorylation and fatty acid beta-oxidation. In this case, anaerobic respiration became the major source of energy metabolism by producing abundant lactate. Conclusively, the simulation based PtPIM method demonstrates a strategy to broaden metabolite coverage in isotope tracing analysis independent of standard chemicals.
    Keywords:  (13)C(6)-glucose tracing; Isotope labeling; Mass spectrometry; Pseudo-targeted Metabolomics; Simulated ion transitions
    DOI:  https://doi.org/10.1016/j.chroma.2023.463923
  5. J Proteome Res. 2023 Apr 04.
    Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry.
    Yuan Liu, Hua Zhang, William F Dove, Zicong Wang, Zhijun Zhu, Perry J Pickhardt, Mark Reichelderfer, Lingjun Li.
      A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.
    Keywords:  colorectal cancer; isobaric tag; mass spectrometry; metabolomics; multiplex labeling; serum biomarker
    DOI:  https://doi.org/10.1021/acs.jproteome.3c00006
  6. J Proteome Res. 2023 Apr 03.
    Quantification of 782 Plasma Peptides by Multiplexed Targeted Proteomics.
    Antoine Lesur, François Bernardin, Eric Koncina, Elisabeth Letellier, Gary Kruppa, Pierre-Olivier Schmit, Gunnar Dittmar.
      Blood analysis is one of the foundations of clinical diagnostics. In recent years, the analysis of proteins in blood samples by mass spectrometry has taken a jump forward in terms of sensitivity and the number of identified proteins. The recent development of parallel reaction monitoring with parallel accumulation and serial fragmentation (prm-PASEF) combines ion mobility as an additional separation dimension. This increases the proteome coverage while allowing the use of shorter chromatographic gradients. To demonstrate the method's full potential, we used an isotope-labeled synthetic peptide mix of 782 peptides, derived from 579 plasma proteins, spiked into blood plasma samples with a prm-PASEF measurement allowing the quantification of 565 plasma proteins by targeted proteomics. As a less time-consuming alternative to the prm-PASEF method, we describe guided data independent acquisition (dia)-PASEF (g-dia-PASEF) and compare its application to prm-PASEF for measuring blood plasma. To demonstrate both methods' performance in clinical samples, 20 patient plasma samples from a colorectal cancer (CRC) cohort were analyzed. The analysis identified 14 differentially regulated proteins between the CRC patient and control individual plasma samples. This shows the technique's potential for the rapid and unbiased screening of blood proteins, abolishing the need for the preselection of potential biomarker proteins.
    Keywords:  CRC; DIA; PASEF; PRM; SIL peptides; biomarker; colorectal cancer; plasma; targeted proteomics
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00575
  7. Trends Cancer. 2023 Apr 05. pii: S2405-8033(23)00032-8. [Epub ahead of print]
    Stearoyl coenzyme A desaturase-1: multitasker in cancer, metabolism, and ferroptosis.
    Utsav Sen, Charles Coleman, Triparna Sen.
      Cancer progression is a highly balanced process and is maintained by a sequence of finely tuned metabolic pathways. Stearoyl coenzyme A desaturase-1 (SCD1), the fatty enzyme that converts saturated fatty acids into monounsaturated fatty acids, is a critical modulator of the fatty acid metabolic pathway. SCD1 expression is associated with poor prognosis in several cancer types. SCD1 triggers an iron-dependent cell death called ferroptosis and elevated levels of SCD1 protect cancer cells against ferroptosis. Pharmacological inhibition of SCD1 as monotherapy and in combination with chemotherapeutic agents shows promising antitumor potential in preclinical models. In this review, we summarize the role of SCD in cancer cell progression, survival, and ferroptosis and discuss potential strategies to exploit SCD1 inhibition in future clinical trials.
    Keywords:  NSCLC; SCD1; cancer therapy; fatty acid metabolism; ferroptosis; immunotherapy
    DOI:  https://doi.org/10.1016/j.trecan.2023.03.003
  8. Front Mol Biosci. 2023 ;10 1112521
    Integrating the potential of ion mobility spectrometry-mass spectrometry in the separation and structural characterisation of lipid isomers.
    Sandra M Camunas-Alberca, Maria Moran-Garrido, Jorge Sáiz, Alberto Gil-de-la-Fuente, Coral Barbas, Ana Gradillas.
      It is increasingly evident that a more detailed molecular structure analysis of isomeric lipids is critical to better understand their roles in biological processes. The occurrence of isomeric interference complicates conventional tandem mass spectrometry (MS/MS)-based determination, necessitating the development of more specialised methodologies to separate lipid isomers. The present review examines and discusses recent lipidomic studies based on ion mobility spectrometry combined with mass spectrometry (IMS-MS). Selected examples of the separation and elucidation of structural and stereoisomers of lipids are described based on their ion mobility behaviour. These include fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids. Recent approaches for specific applications to improve isomeric lipid structural information using direct infusion, coupling imaging, or liquid chromatographic separation workflows prior to IMS-MS are also discussed, including: 1) strategies to improve ion mobility shifts; 2) advanced tandem MS methods based on activation of lipid ions with electrons or photons, or gas-phase ion-molecule reactions; and 3) the use of chemical derivatisation techniques for lipid characterisation.
    Keywords:  identification; ion mobility spectrometry (IMS); lipid isomers; lipidomics; mass spectrometry (MS); separation; stereoisomers; structural isomers
    DOI:  https://doi.org/10.3389/fmolb.2023.1112521
  9. Magn Reson Chem. 2023 Apr 02.
    Multiplatform Untargeted Metabolomics.
    Micah J Jeppesen, Robert Powers.
      Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.
    Keywords:  mass spectrometry; metabolite assignment; metabolome coverage; metabolomics; multiplatform; nuclear magnetic resonance
    DOI:  https://doi.org/10.1002/mrc.5350
  10. Data Brief. 2023 Jun;48 109089
    Targeted lipidomics data of COVID-19 patients.
    Michele Costanzo, Marianna Caterino.
      The dataset provided with this article describes a targeted lipidomics analysis performed on the serum of COVID-19 patients characterized by different degree of severity. As the ongoing pandemic has posed a challenging threat for humanity, the data here presented belong to one of the first lipidomics studies carried out on COVID-19 patients' samples collected during the first pandemic waves. Serum samples were obtained from hospitalized patients with a molecular diagnosis of SARS-CoV-2 infection detected after nasal swab, and categorized as mild, moderate, or severe according to pre-established clinical descriptors. The MS-based targeted lipidomic analysis was performed by MRM using a Triple Quad 5500+ mass spectrometer, and the quantitative data were acquired on a panel of 483 lipids. The characterization of this lipidomic dataset has been outlined using multivariate and univariate descriptive statistics and bioinformatics tools.
    Keywords:  COVID-19 research; COVIDomics; Lipid metabolism; Lipidomics; Lipids mass spectrometry; Multiple reaction monitoring; Serum lipidome; Targeted metabolomics
    DOI:  https://doi.org/10.1016/j.dib.2023.109089
  11. Mol Cell Proteomics. 2023 Mar 31. pii: S1535-9476(23)00048-8. [Epub ahead of print] 100538
    MSFragger-Labile: A Flexible Method to Improve Labile PTM Analysis in Proteomics.
    Daniel A Polasky, Daniel J Geiszler, Fengchao Yu, Kai Li, Guo Ci Teo, Alexey I Nesvizhskii.
      Post-translational modifications of proteins play essential roles in defining and regulating the functions of the proteins they decorate, making identification of these modifications critical to understanding biology and disease. Methods for enriching and analyzing a wide variety of biological and chemical modifications of proteins have been developed using mass spectrometry (MS)-based proteomics, largely relying on traditional database search methods to identify the resulting mass spectra of modified peptides. These database search methods treat modifications as static attachments of a mass to particular position in the peptide sequence, but many modifications undergo fragmentation in tandem MS experiments alongside, or instead of, the peptide backbone. While this fragmentation can confound traditional search methods, it also offers unique opportunities for improved searches that incorporate modification-specific fragment ions. Here, we present a new Labile Mode in the MSFragger search engine that provides the flexibility to tailor modification-centric searches to the fragmentation observed. We show that labile mode can dramatically improve spectrum identification rates of phosphopeptides, RNA-crosslinked peptides, and ADP-ribosylated peptides. Each of these modifications presents distinct fragmentation characteristics, showcasing the flexibility of MSFragger labile mode to improve search for a wide variety of biological and chemical modifications.
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100538
  12. Nat Methods. 2023 Apr 03.
    Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics.
    R Gray Huffman, Andrew Leduc, Christoph Wichmann, Marco Di Gioia, Francesco Borriello, Harrison Specht, Jason Derks, Saad Khan, Luke Khoury, Edward Emmott, Aleksandra A Petelski, David H Perlman, Jürgen Cox, Ivan Zanoni, Nikolai Slavov.
      Major aims of single-cell proteomics include increasing the consistency, sensitivity and depth of protein quantification, especially for proteins and modifications of biological interest. Here, to simultaneously advance all these aims, we developed prioritized Single-Cell ProtEomics (pSCoPE). pSCoPE consistently analyzes thousands of prioritized peptides across all single cells (thus increasing data completeness) while maximizing instrument time spent analyzing identifiable peptides, thus increasing proteome depth. These strategies increased the sensitivity, data completeness and proteome coverage over twofold. The gains enabled quantifying protein variation in untreated and lipopolysaccharide-treated primary macrophages. Within each condition, proteins covaried within functional sets, including phagosome maturation and proton transport, similarly across both treatment conditions. This covariation is coupled to phenotypic variability in endocytic activity. pSCoPE also enabled quantifying proteolytic products, suggesting a gradient of cathepsin activities within a treatment condition. pSCoPE is freely available and widely applicable, especially for analyzing proteins of interest without sacrificing proteome coverage. Support for pSCoPE is available at http://scp.slavovlab.net/pSCoPE .
    DOI:  https://doi.org/10.1038/s41592-023-01830-1
  13. Cell Metab. 2023 Apr 04. pii: S1550-4131(23)00085-2. [Epub ahead of print]35(4): 711-721.e4
    Global determination of reaction rates and lipid turnover kinetics in Mus musculus.
    Qishan Chen, Hu Li, He Tian, Sin Man Lam, Yilie Liao, Ziyin Zhang, Manyuan Dong, Shaoru Chen, Yuxiao Yao, Jiemiao Meng, Yong Zhang, Lemin Zheng, Zhuo-Xian Meng, Weiping Han, Guanghou Shui, Dahai Zhu, Suneng Fu.
      Metabolism is fundamental to life, but measuring metabolic reaction rates remains challenging. Here, we applied C13 fluxomics to monitor the metabolism of dietary glucose carbon in 12 tissues, 9 brain compartments, and over 1,000 metabolite isotopologues over a 4-day period. The rates of 85 reactions surrounding central carbon metabolism are determined with elementary metabolite unit (EMU) modeling. Lactate oxidation, not glycolysis, occurs at a comparable pace with the tricarboxylic acid cycle (TCA), supporting lactate as the primary fuel. We expand the EMU framework to track and quantify metabolite flows across tissues. Specifically, multi-organ EMU simulation of uridine metabolism shows that tissue-blood exchange, not synthesis, controls nucleotide homeostasis. In contrast, isotopologue fingerprinting and kinetic analyses reveal the brown adipose tissue (BAT) having the highest palmitate synthesis activity but no apparent contribution to circulation, suggesting a tissue-autonomous synthesis-to-burn mechanism. Together, this study demonstrates the utility of dietary fluxomics for kinetic mapping in vivo and provides a rich resource for elucidating inter-organ metabolic cross talk.
    Keywords:  dietary fluxomics; elementary metabolite units; inter-organ metabolite flow; multi-organ EMU modeling
    DOI:  https://doi.org/10.1016/j.cmet.2023.03.007
  14. Clin Chem Lab Med. 2023 Apr 04.
    Improved diagnostics of purine and pyrimidine metabolism disorders using LC-MS/MS and its clinical application.
    Alessio Cremonesi, David Meili, Anahita Rassi, Martin Poms, Barbara Tavazzi, Václava Škopová, Johannes Häberle, Marie Zikánová, Martin Hersberger.
       OBJECTIVES: To develop a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify 41 different purine and pyrimidine (PuPy) metabolites in human urine to allow detection of most known disorders in this metabolic pathway and to determine reference intervals.
    METHODS: Urine samples were diluted with an aqueous buffer to minimize ion suppression. For detection and quantification, liquid chromatography was combined with electrospray ionization, tandem mass spectrometry and multiple reaction monitoring. Transitions and instrument settings were established to quantify 41 analytes and nine stable-isotope-labeled internal standards (IS).
    RESULTS: The established method is precise (intra-day CV: 1.4-6.3%; inter-day CV: 1.3-15.2%), accurate (95.2% external quality control results within ±2 SD and 99.0% within ±3 SD; analyte recoveries: 61-121%), sensitive and has a broad dynamic range to quantify normal and pathological metabolite concentrations within one run. All analytes except aminoimidazole ribonucleoside (AIr) are stable before, during and after sample preparation. Moreover, analytes are not affected by five cycles of freeze-thawing (variation: -5.6 to 7.4%), are stable in thymol (variation: -8.4 to 12.9%) and the lithogenic metabolites also in HCl conserved urine. Age-dependent reference intervals from 3,368 urine samples were determined and used to diagnose 11 new patients within 7 years (total performed tests: 4,206).
    CONCLUSIONS: The presented method and reference intervals enable the quantification of 41 metabolites and the potential diagnosis of up to 25 disorders of PuPy metabolism.
    Keywords:  LC-MS/MS; diagnosis; purines; pyrimidines; reference intervals; stability
    DOI:  https://doi.org/10.1515/cclm-2022-1236
  15. Nat Metab. 2023 Apr 03.
    Triglyceride cycling enables modification of stored fatty acids.
    Klaus Wunderling, Jelena Zurkovic, Fabian Zink, Lars Kuerschner, Christoph Thiele.
      Triglyceride cycling is the process of continuous degradation and re-synthesis of triglyceride in cellular stores. We show in 3T3-L1 adipocytes that triglycerides are subject to rapid turnover and re-arrangement of fatty acids with an estimated half-life of 2-4 h. We develop a tracing technology that can simultaneously and quantitatively follow the metabolism of multiple fatty acids to study the triglyceride futile substrate cycle directly and with molecular species resolution. Our approach is based on alkyne fatty acid tracers and mass spectrometry. The triglyceride cycling is connected to modification of released fatty acids by elongation and desaturation. Through cycling and modification, saturated fatty acids are slowly converted to monounsaturated fatty acids, and linoleic acid to arachidonic acid. We conclude that triglyceride cycling renders stored fatty acids accessible for metabolic alteration. The overall process facilitates cellular adjustments to the stored fatty acid pool to meet changing needs of the cell.
    DOI:  https://doi.org/10.1038/s42255-023-00769-z
  16. Biochim Biophys Acta Rev Cancer. 2023 Apr 02. pii: S0304-419X(23)00042-2. [Epub ahead of print] 188893
    The role of amino acid metabolism alterations in pancreatic cancer: From mechanism to application.
    Shenao Fu, Shaokang Xu, Shubing Zhang.
      The incidence of pancreatic cancer is increasing in both developed and developing Nations. In recent years, various research evidence suggested that reprogrammed metabolism may play a key role in pancreatic cancer tumorigenesis and development. Therefore, it has great potential as a diagnostic, prognostic and therapeutic target. Amino acid metabolism is deregulated in pancreatic cancer, and changes in amino acid metabolism can affect cancer cell status, systemic metabolism in malignant tumor patients and mistakenly involved in different biological processes including stemness, proliferation and growth, invasion and migration, redox state maintenance, autophagy, apoptosis and even tumor microenvironment interaction. Generally, the above effects are achieved through two pathways, energy metabolism and signal transduction. This review aims to highlight the current research progress on the abnormal alterations of amino acids metabolism in pancreatic cancer, how they affect tumorigenesis and development of pancreatic cancer and the application prospects of them as diagnostic, prognostic and therapeutic targets.
    Keywords:  Amino acid metabolism; Apoptosis; Autophagy; Cellular redox homeostasis; Pancreatic cancer; Tumor microenvironment; mTOR signaling
    DOI:  https://doi.org/10.1016/j.bbcan.2023.188893
  17. Electrophoresis. 2023 Apr 04.
    Lipidomic study and diagnosis of hepatocellular carcinoma tumor with rapid evaporative ionization mass spectrometry.
    Haixing Wang, Ting Li, Qing Shen, Zhifang Liu, You-Wei Chen, Darong Huang, Jiancheng Yu, Long Wang.
      Liver cancer is generally considered the leading cause of cancer deaths worldwide, and hepatocellular carcinoma (HCC) contributes to more than 90% of liver cancers. The altered lipid metabolism for rapid cancer cell growth and tumor formation has been frequently proven. In this study, an ambient ionization mass spectrometry technique, rapid evaporative ionization mass spectrometry (REIMS) using a monopolar electric knife, called iKnife, was systematically optimized and employed for ex vivo analysis of 12 human HCC tumor tissue specimens together with the paired paracancerous tissue (PT) and noncancerous-liver-tissue (NCT) specimens. Nine free fatty acids and thirty-four phospholipids were tentatively identified according to their extract masses and/or tandem mass spectra. With the help of statistical methods, seven free fatty acids and ten phospholipids were distributed differently in three types of liver tissue specimens (95% confidence interval, CI). The box plots showed these characterized lipid metabolites varied in PT, HCC, and NCT. Compared with PT and NCT, the upregulation of four common fatty acids FA 18:0, FA 20:4, FA 16:0, and FA 18:1, together with phospholipids PC 36:1, PE 38:3, PE (18:0/20:4), PA (O-36:1), PC (32:1), PC 32:0, PE 34:0 and PC (16:0/18:1) were found in HCC specimens. The sensitivity and specificity of the established statistic model for real-time HCC tumor diagnosis were 100% and 90.5%, respectively. This study demonstrated that the described REIMS technique is a potential method for rapid lipidomic analysis and characterization of HCC tumor tissue. This article is protected by copyright. All rights reserved.
    Keywords:  fatty acid; hepatocellular carcinoma (HCC); lipidomics; phospholipid; rapid evaporative ionization mass spectrometry (REIMS)
    DOI:  https://doi.org/10.1002/elps.202300007
  18. Nat Metab. 2023 Apr 06.
    The GAPDH redox switch safeguards reductive capacity and enables survival of stressed tumour cells.
    Deepti Talwar, Colin G Miller, Justus Grossmann, Lukasz Szyrwiel, Torsten Schwecke, Vadim Demichev, Ana-Matea Mikecin Drazic, Anand Mayakonda, Pavlo Lutsik, Carmen Veith, Michael D Milsom, Karin Müller-Decker, Michael Mülleder, Markus Ralser, Tobias P Dick.
      Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is known to contain an active-site cysteine residue undergoing oxidation in response to hydrogen peroxide, leading to rapid inactivation of the enzyme. Here we show that human and mouse cells expressing a GAPDH mutant lacking this redox switch retain catalytic activity but are unable to stimulate the oxidative pentose phosphate pathway and enhance their reductive capacity. Specifically, we find that anchorage-independent growth of cells and spheroids is limited by an elevation of endogenous peroxide levels and is largely dependent on a functional GAPDH redox switch. Likewise, tumour growth in vivo is limited by peroxide stress and suppressed when the GAPDH redox switch is disabled in tumour cells. The induction of additional intratumoural oxidative stress by chemo- or radiotherapy synergized with the deactivation of the GAPDH redox switch. Mice lacking the GAPDH redox switch exhibit altered fatty acid metabolism in kidney and heart, apparently in compensation for the lack of the redox switch. Together, our findings demonstrate the physiological and pathophysiological relevance of oxidative GAPDH inactivation in mammals.
    DOI:  https://doi.org/10.1038/s42255-023-00781-3
  19. J Proteome Res. 2023 Apr 04.
    Malondialdehyde-Induced Post-Translational Modification of Human Hemoglobin.
    Dimitrios Tsikas.
      Lysine residues in proteins undergo multiple enzymatic and nonenzymatic post-translational modifications (PTMs). The terminal ε amine group of lysine residues in proteins is carbonylated chemically by carbonyl species such as glyoxal (GO; OCH-CHO, C2H2O2; MW 58) and methylglyoxal (MGO; OCH-C(=O)-CH3, C3H4O2; MW 72) that are derived from the metabolism of endogenous substances including glucose. The dicarbonyl species malondialdehyde (MDA, OCH-CH2-CHO, C3H4O2; MW 72) is generated by enzymatic and nonenzymatic peroxidation of polyunsaturated fatty acids (PUFAs). GO, MGO, and MDA occur in biological systems in their free forms and in their conjugated forms adducted to free amino acids and amino acid residues in proteins, notably to lysine. MDA is a C-H-acidic acid (pKa, 4.45). Biological MDA is widely used as a biomarker of lipid peroxidation. The most frequently analyzed biological samples for MDA are plasma and serum. Reportedly, MDA concentrations in plasma and serum samples of healthy and ill humans range by several orders of magnitude. The most severe preanalytical contributor is artificial formation of MDA in lipid-rich samples such as plasma and serum. In very few publications, plasma MDA concentrations were reported to lie in the lower mM-range.
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00764
  20. Methods Mol Biol. 2023 ;2620 229-241
    Identification of Protein Arginylation by Encapsulated N-Terminal Peptide Enrichment Method.
    Shinyeong Ju, Cheolju Lee.
      Mass spectrometric analysis of N-terminal peptides reveals altered amino acid sequences at the protein's N-terminus and the presence of posttranslational modifications (PTM). Recent advancement in enriching N-terminal peptides facilitates the discovery of rare N-terminal PTMs in samples with restricted availability. In this chapter, we describe a simple, single-stage oriented N-terminal peptide enrichment method that helps the overall sensitivity of N-terminal peptides. In addition, we describe how to increase the depth of identification, to use software to identify and quantify N-terminally arginylated peptides.
    Keywords:  Mass spectrometry; N-terminal arginylation; N-terminal peptide enrichment; N-terminomics; Proteomics; iNrich
    DOI:  https://doi.org/10.1007/978-1-0716-2942-0_25
  21. Methods Mol Biol. 2023 ;2620 153-155
    Analysis of Arginylated Peptides by Subtractive Edman Degradation.
    Anna S Kashina, John R Yates Iii.
      During the early studies of N-terminal arginylation, Edman degradation was widely used to identify N-terminally added Arg on protein substrates. This old method is reliable, but highly depends on the purity and abundance of samples and can become misleading unless a highly purified highly arginylated protein can be obtained. Here, we report a mass spectrometry-based method that utilizes Edman degradation chemistry to identify arginylation in more complex and less abundant protein samples. This method can also apply to the analysis of other posttranslational modifications.
    Keywords:  Arginylation; Edman degradation; Mass spectrometry
    DOI:  https://doi.org/10.1007/978-1-0716-2942-0_20
  22. Life Sci. 2023 Mar 31. pii: S0024-3205(23)00260-6. [Epub ahead of print]322 121626
    A metabolomics approach to the validation of predictive metabolites and phenotypic expression in non-alcoholic fatty liver disease.
    Raja Ganesan, Haripriya Gupta, Jin-Ju Jeong, Satya Priya Sharma, Sung-Min Won, Ki-Kwang Oh, Sang Jun Yoon, Dong Joon Kim, Ki Tae Suk.
       AIMS: Nonalcoholic fatty liver disease (NAFLD) is becoming more common and severe. Individuals with NAFLD have an altered composition of gut- microbial metabolites. We used metabolomics profiling to identify microbial metabolites that could indicate gut-liver metabolic severity. Noninvasive biomarkers are required for NAFLD, especially for patients at high risk of disease progression.
    MAIN METHODS: We compared the stool metabolomes, untargeted metabolomics, and clinical data of 80 patients. Patients with nonalcoholic fatty liver (NAFL: n = 16), nonalcoholic steatohepatitis (NASH: n = 26), and cirrhosis (n = 19) and healthy control individuals (HC: n = 19) were enrolled. The identified metabolites in NAFLD were evaluated by multivariate statistical analysis and metabolic pathotypic expression. Gas chromatography-mass spectrometry (GC-MS) and liquid chromatography coupled to time-of-flight-mass spectrometry (LC-TOF-MS) were used to analyze metabolites.
    KEY FINDINGS: Untargeted metabolomics was used to identify and quantify 103 metabolites. Principal component analysis (PCA) was used to assess the metabolic discrimination of NAFL, NASH, and cirrhosis. Short-chain fatty acids (SCFA) levels were significantly lower in NAFLD patients, including those of acetate (p = 0.03), butyrate (p = 0.0008), and propionate. The stool cholic acid (p = 0.001) level was significantly increased in NAFLD patients. Palmitoylcarnitine and l-carnitine levels were significantly increased in NASH and cirrhosis patients. The phenotypic expression of these metabolites was linked to β-oxidation.
    SIGNIFICANCE: We demonstrated a distinct metabolome profile in NAFLD patients with NAFL, NASH, and cirrhosis. We also discovered that the expression of certain metabolites and metabolic pathways was linked to NAFLD.
    Keywords:  Cirrhosis; Metabolic discriminations; Metabolic syndrome; Metabolomics; NAFL; NAFLD; NASH; Untargeted metabolic activity
    DOI:  https://doi.org/10.1016/j.lfs.2023.121626
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